Researchers from China, Belgium, the US, and South Africa report on findings from a genome sequence analysis of Crucihimalaya himalaica, a plant that grows on the Qinghai-Tibet Plateau. Using short- and long-read sequences, the team put together a nearly 235 million-base C. himalaica genome assembly containing an estimated 27,019 protein-coding genes, and hundreds of microRNAs, ribosomal RNAs, and small nuclear RNAs. Through comparisons with related Arabidopsis and Capsella plants, and a phylogenetic analysis focused on almost 4,600 single-copy genes, they suggested C. himalaica and Capsella split from the lineage leading to Arabidopsis roughly 12.7 million to 17.2 million years ago, before diverging from one another somewhere between 8.8 million and 12.2 million years ago. The new sequence also offered clues to gene family expansions, contractions, and genes under positive selection in the C. himalaica plants adapted to high altitude, powerful ultraviolet radiation, low temperatures, and other conditions found on the Qinghai-Tibet Plateau.
An international team led by investigators in Hungary explores genetic features involved in multicellularity and fruiting body development in mushroom-forming fungi from the 350 million-year-old Agaricomycetes class. Using transcriptome data for several tissue types at different stages of development in half a dozen fungal species, together with genome sequence data representing more than 200 fungi, the investigators tracked down genes from hundreds of families and dozens of function groups that appeared to be regulated distinctly with development in all or most of the transcriptomically-profiled species. These and other findings presented in the study "outline the major multicellularity-related and developmental processes of mushrooms, including the role of transcriptional reprogramming, gene co-expression networks, and alternative splicing," the authors report, "and reveal significant convergence with other complex multicellular lineages."
Researchers from the Children's Hospital of Philadelphia, University of Pennsylvania, and elsewhere dig into loci previously linked to type 1 diabetes risk through genome-wide association studies. The team used RNA sequencing, low-input histone H3K4me1 and H3K27ac chromatin immunoprecipitation sequencing, and other approaches to fine map these regions, identifying differential gene expression, active transcriptional enhancers, and more in primary T-helper 1 and regulatory T immune cells from six individuals with and five individuals without type 1 diabetes. Using this approach, the authors saw hundreds of differentially-expressed genes and narrowed in on four enhancer-altering SNPs in linkage disequilibrium with lead type 1 diabetes GWAS variants, including two SNPs with allele-specific, immune-related transcription factor binding. "Because many autoimmune diseases share some genetic underpinnings, our dataset may be used to understand causal non-coding mutations in related autoimmune diseases," they write.